code: def maximum_log_likelihood_objective(self) -> tf.Tensor:  # type: ignore[override]
      return self.elbo()
  
imports: from typing import Optional
  import numpy
  import tensorflow
  from check_shapes import check_shapes, inherit_check_shapes
  from ..None import covariances, kernels, likelihoods
  from ..base import InputData, MeanAndVariance, OutputData, Parameter, RegressionData, TensorType
  from ..config import default_float, default_jitter
  from ..expectations import expectation
  from ..inducing_variables import InducingPoints
  from ..kernels import Kernel
  from ..mean_functions import MeanFunction, Zero
  from ..probability_distributions import DiagonalGaussian
  from ..utilities import assert_params_false, positive, to_default_float
  from ..utilities.ops import pca_reduce
  from .gpr import GPR
  from .model import GPModel
  from .training_mixins import InternalDataTrainingLossMixin
  from .util import InducingVariablesLike, data_input_to_tensor, inducingpoint_wrapper
label_desc: Use image node_id 2 for calling the BayesianGPLVM obj's underlying member method code with example usage: obj.maximum_log_likelihood_objective() and returns: self